Abstract
Although most of the clustering literature focuses on one-sided clustering algorithms, simultaneous clustering has recently gained attention as a powerful tool that allows to circumvent some limitations of classical clustering approach. Simultaneous clustering methods perform clustering in the two dimensions simultaneously. In this paper, we introduce a large number of existing simultaneous clustering approaches applied in bioinformatics as well as in text mining, web mining and information retrieval and classify them in accordance with the methods used to perform the clustering and the target applications.
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Charrad, M., Ben Ahmed, M. (2011). Simultaneous Clustering: A Survey. In: Kuznetsov, S.O., Mandal, D.P., Kundu, M.K., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2011. Lecture Notes in Computer Science, vol 6744. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21786-9_60
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DOI: https://doi.org/10.1007/978-3-642-21786-9_60
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